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Current literature dealing with the theory of sampling process flows is limited in scope, a situation addressed by papers presented at conferences by the author. This paper provides a summary of methods to quantify process sampling variance in a sound statistical manner. Two methods of calculation of the process sampling variance are presented here with models for robust estimation of the process covariance/variogram. The strategies for process sampling to acquire the data for process characterisation are described. The method for process characterisation can be based on special sampling campaigns, on the analysis of on-line measurement data, or on the analysis of historical data, which may be based on composite samples, such as shift samples. These scenarios are all dealt with as well as methods based on analysis of process dynamics. The latter analysis demonstrates that use of covariance functions drawn from geostatistical practice can be inappropriate for process analysis. The work is supported with plant data examples and quantitative analyses of process conditions. [ABSTRACT FROM AUTHOR]

Aims: This article aims to perform a Systematic Literature Review (SLR) to better understand the structures of different methods, techniques, models, methodologies, and technologies related to provenance data management in health information systems (HISs). The SLR developed here seeks to answer the questions that contribute to describing the results. Method: An SLR was performed on six databases using a search string. The backward and forward snowballing technique was also used. Eligible studies were all articles in English that presented on the use of different methods, techniques, models, methodologies, and technologies related to provenance data management in HISs. The quality of the included articles was assessed to obtain a better connection to the topic studied. Results: Of the 239 studies retrieved, 14 met the inclusion criteria described in this SLR. In order to complement the retrieved studies, 3 studies were included using the backward and forward snowballing technique, totaling 17 studies dedicated to the construction of this research. Most of the selected studies were published as conference papers, which is common when involving computer science in HISs. There was a more frequent use of data provenance models from the PROV family in different HISs combined with different technologies, among which blockchain and middleware stand out. Despite the advantages found, the lack of technological structure, data interoperability problems, and the technical unpreparedness of working professionals are still challenges encountered in the management of provenance data in HISs. Conclusion: It was possible to conclude the existence of different methods, techniques, models, and combined technologies, which are presented in the proposal of a taxonomy that provides researchers with a new understanding about the management of provenance data in HISs. [ABSTRACT FROM AUTHOR]

In this paper, a systematic literature review is presented, through a survey of the main digital databases, regarding modelling methods for Short-Term Load Forecasting (STLF) for hourly electricity demand for residential electricity and to realize the performance evolution and impact of Artificial Intelligence (AI) in STLF. With these specific objectives, a conceptual framework on the subject was developed, along with a systematic review of the literature based on scientific publications with high impact and a bibliometric study directed towards the scientific production of AI and STLF. The review of research articles over a 10-year period, which took place between 2012 and 2022, used the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) method. This research resulted in more than 300 articles, available in four databases: Web of Science, IEEE Xplore, Scopus, and Science Direct. The research was organized around three central themes, which were defined through the following keywords: STLF, Electricity, and Residential, along with their corresponding synonyms. In total, 334 research articles were analyzed, and the year of publication, journal, author, geography by continent and country, and the area of application were identified. Of the 335 documents found in the initial research and after applying the inclusion/exclusion criteria, which allowed delimiting the subject addressed in the topics of interest for analysis, 38 (thirty-eight) documents were in English (26 journal articles and 12 conference papers). The results point to a diversity of modelling techniques and associated algorithms. The corresponding performance was measured with different metrics and, therefore, cannot be compared directly. Hence, it is desirable to have a unified dataset, together with a set of benchmarks with well-defined metrics for a clear comparison of all the modelling techniques and the corresponding algorithms. [ABSTRACT FROM AUTHOR]

This research focused on using RGB-D images and modifying an existing machine learning network architecture to generate predictions of the location of successfully grasped objects and to optimize the control system for state delays. A five-finger gripper designed to mimic the human palm was tested to demonstrate that it can perform more delicate missions than many two- or three-finger grippers. Experiments were conducted using the 6-DOF robot arm with the five-finger and two-finger grippers to perform at least 100 actual machine grasps, and compared to the results of other studies. Additionally, we investigated state time delays and proposed a control method for a robot manipulator. Many studies on time-delay systems have been conducted, but most focus on input and output delays. One reason for this emphasis is that input and output delays are the most commonly occurring delays in physical or electronic systems. An additional reason is that state delays increase the complexity of the overall control system. Finally, it was demonstrated that our network can perform as well as a deep network architecture with little training data and omitting steps, such as posture evaluation, and when combined with the hardware advantages of the five-finger gripper, it can produce an automated system with a gripping success rate of over 90%. This paper is an extended study of the conference paper. [ABSTRACT FROM AUTHOR]

Handwritten signatures are widely used for identity authorization. However, verifying handwritten signatures is cumbersome in practice due to the dependency on extra drawing tools such as a digitizer, and because the false acceptance of a forged signature can cause damage to property. Therefore, exploring a way to balance the security and user experiment of handwritten signatures is critical. In this paper, we propose a handheld signature verification scheme called SilentSign, which leverages acoustic sensors (i.e., microphone and speaker) in mobile devices. Compared to the previous online signature verification system, it provides handy and safe paper-based signature verification services. The prime notion is to utilize the acoustic signals that are bounced back via a pen tip to depict a user's signing pattern. We designed the signal modulation stratagem carefully to guarantee high performance, developed a distance measurement algorithm based on phase shift, and trained a verification model. In comparison with the traditional signature verification scheme, SilentSign allows users to sign more conveniently as well as invisibly. To evaluate SilentSign in various settings, we conducted comprehensive experiments with 35 participants. Our results reveal that SilentSign can attain 98.2 % AUC and 1.25 % EER. We note that a shorter conference version of this paper was presented in Percom (2019). Our initial conference paper did not finish the complete experiment. This manuscript has been revised and provided additional experiments to the conference proceedings; for example, by including System Robustness, Computational Overhead, etc. [ABSTRACT FROM AUTHOR]

The pathophysiology of chronic rhinosinusitis (CRS) is multifactorial and not entirely clear. The objective of the review was to examine the current state of knowledge concerning the role of exosomes in CRS. For this systematic review, we searched PubMed/MEDLINE, Scopus, CENTRAL, and Web of Science databases for studies published until 7 August 2022. Only original research articles describing studies published in English were included. Reviews, book chapters, case studies, conference papers, and opinions were excluded. The quality of the evidence was assessed with the modified Office and Health Assessment and Translation (OHAT) Risk of Bias Rating Tool for Human and Animal Studies. Of 250 records identified, 17 were eligible, all of which had a low to moderate risk of overall bias. Presented findings indicate that exosomal biomarkers, including proteins and microRNA, act as promising biomarkers in the diagnostics and prognosis of CRS patients and, in addition, may contribute to finding novel therapeutic targets. Exosomes reflecting tissue proteomes are excellent, highly available material for studying proteomic alterations noninvasively. The first steps have already been taken, but more advanced research on nasal exosomes is needed, which might open a wider door for individualized medicine in CRS. [ABSTRACT FROM AUTHOR]

Biodiesel can be produced from vegetable oils, animal fats, frying oils, and from microorganism-synthesized oils. These sources render biodiesel an easily biodegradable fuel. The aim of this work was to perform an advanced bibliometric analysis of primary studies relating to biodiesel production worldwide by identifying the key countries and regions that have shown a strong engagement in this area, and by understanding the dynamics of their collaboration and research outputs. Additionally, an assessment of the main primary feedstocks employed in this research was carried out, along with an analysis of the current and future trends that are expected to define new paths and methodologies to be used in the manufacture of biodegradable and renewable fuels. A total of 4586 academic outputs were selected, including peer-reviewed research articles, conference papers, and literature reviews related to biodiesel production, in the time period spanning from 2010 to 2021. Articles that focused on feedstocks for the production of biodiesel were also included, with a search that returned 330 papers. Lastly, 60 articles relating to biodiesel production via sewage were specifically included to allow for an analysis of this source as a promising feedstock in the future of the biofuel market. Via the geocoding and the document analyses performed, we concluded that China, Malaysia, and India are the largest writers of articles in this area, revealing a great interest in biofuels in Asia. Additionally, it was noted that environmental concerns have caused authors to conduct research on feedstocks that can address the sustainability challenges in the production of biodiesel. [ABSTRACT FROM AUTHOR]

We try to assess the validity of assumptions taken when deriving drift velocity. We give simple formulas for characteristics of the spatiotemporal correlation function of the observed diffraction pattern for the frozen flow and the more general Briggs model. Using Low-Frequency Array (LOFAR) Cassiopeia intensity observation, we compare the experimental velocity scaling factor with a theoretical one to show that both models do not follow observations. We also give a qualitative comparison of our drift velocity estimates with SuperDARN convection maps. The article is essentially an extended version of the conference paper: "Determining ionospheric drift and anisotropy of irregularities from LOFAR core measurements", Signal Processing Symposium 2021 (SPSympo 2021). [ABSTRACT FROM AUTHOR]

The technology for transcranial magnetic stimulation (TMS) has significantly changed over the years, with important improvements in the signal generators, the coils, the positioning systems, and the software for modeling, optimization, and therapy planning. In this systematic literature review (SLR), the evolution of each component of TMS technology is presented and analyzed to assess the limitations to overcome. This SLR was carried out following the PRISMA 2020 statement. Published articles of TMS were searched for in four databases (Web of Science, PubMed, Scopus, IEEE). Conference papers and other reviews were excluded. Records were filtered using terms about TMS technology with a semi-automatic software; articles that did not present new technology developments were excluded manually. After this screening, 101 records were included, with 19 articles proposing new stimulator designs (18.8%), 46 presenting or adapting coils (45.5%), 18 proposing systems for coil placement (17.8%), and 43 implementing algorithms for coil optimization (42.6%). The articles were blindly classified by the authors to reduce the risk of bias. However, our results could have been influenced by our research interests, which would affect conclusions for applications in psychiatric and neurological diseases. Our analysis indicates that more emphasis should be placed on optimizing the current technology with a special focus on the experimental validation of models. With this review, we expect to establish the base for future TMS technological developments. [ABSTRACT FROM AUTHOR]

Definition: This entry presents the theoretical fundamentals, the mathematical formulation, and the numerical solution for the problem of desiccation cracks in clayey soils. The formulation uses two stress state variables (total stress and suction) and results in a non-symmetric and nonlinear system of transient partial differential equations. A release node algorithm technique is proposed to simulate cracking, and the strategy to implement it in the hydromechanical framework is explained in detail. This general framework was validated with experimental results, and several numerical examples were published at international conferences and in journal papers. [ABSTRACT FROM AUTHOR]

Federated learning (FL) is a scheme in which several consumers work collectively to unravel machine learning (ML) problems, with a dominant collector synchronizing the procedure. This decision correspondingly enables the training data to be distributed, guaranteeing that the individual device's data are secluded. The paper systematically reviewed the available literature using the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guiding principle. The study presents a systematic review of appliable ML approaches for FL, reviews the categorization of FL, discusses the FL application areas, presents the relationship between FL and Blockchain Technology (BT), and discusses some existing literature that has used FL and ML approaches. The study also examined applicable machine learning models for federated learning. The inclusion measures were (i) published between 2017 and 2021, (ii) written in English, (iii) published in a peer-reviewed scientific journal, and (iv) Preprint published papers. Unpublished studies, thesis and dissertation studies, (ii) conference papers, (iii) not in English, and (iv) did not use artificial intelligence models and blockchain technology were all removed from the review. In total, 84 eligible papers were finally examined in this study. Finally, in recent years, the amount of research on ML using FL has increased. Accuracy equivalent to standard feature-based techniques has been attained, and ensembles of many algorithms may yield even better results. We discovered that the best results were obtained from the hybrid design of an ML ensemble employing expert features. However, some additional difficulties and issues need to be overcome, such as efficiency, complexity, and smaller datasets. In addition, novel FL applications should be investigated from the standpoint of the datasets and methodologies. [ABSTRACT FROM AUTHOR]

Process variations during manufacturing lead to differences in the performance of the chips. In order to better utilize the performance of the chips, it is necessary to perform maximum operation frequency ( F m a x ) tests to place the chips into different speed bins. For most F m a x tests, significant efforts are put in place to reduce test cost and improve binning accuracy; e.g., our conference paper published in ICICM 2017 presents a novel binning sensor for low-cost and accurate speed binning. However, by promoting chips placed at the lower bins, because of conservative binning, into higher bins, the overall profit can greatly increase. Therefore, this paper, extended based on a conference paper, presents a novel and adaptive methodology for speed binning, in which the paths impacting the speed bin of a specific IC are identified and adapted by our proposed on-chip Binning Checker and Binning Adaptor. As a result, some parts at a bin margin can be promoted to higher bins. The proposed methodology can be used to optimize the F m a x yield of a digital circuit when it has redundant timing in clock tree, and it can be integrated into current F m a x tests with low extra cost. The proposed adaptive system has been implemented and validated on five benchmarks from ITC, ISCAS89, and OpenSPARCT2 core on 28 nm Altera FPGAs. Measurement results show that the number of higher bin chips is improved by 7–16%, and our cost analysis shows that the profit increase is between 1.18% and 3.04%. [ABSTRACT FROM AUTHOR]

Silver nanoparticles (AgNPs) have been employed in various fields of biotechnology due to their proven properties as an antibacterial, antiviral and antifungal agent. AgNPs are generally synthesized through chemical, physical and biological approaches involving a myriad of methods. As each approach confers unique advantages and challenges, a trends analysis of literature for the AgNPs synthesis using different types of synthesis were also reviewed through a bibliometric approach. A sum of 10,278 publications were analyzed on the annual numbers of publication relating to AgNPs and biological, chemical or physical synthesis from 2010 to 2020 using Microsoft Excel applied to the Scopus publication database. Furthermore, another bibliometric clustering and mapping software were used to study the occurrences of author keywords on the biomedical applications of biosynthesized AgNPs and a total collection of 224 documents were found, sourced from articles, reviews, book chapters, conference papers and reviews. AgNPs provides an excellent, dependable, and effective solution for seven major concerns: as antibacterial, antiviral, anticancer, bone healing, bone cement, dental applications and wound healing. In recent years, AgNPs have been employed in biomedical sector due to their antibacterial, antiviral and anticancer properties. This review discussed on the types of synthesis, how AgNPs are characterized and their applications in biomedical field. [ABSTRACT FROM AUTHOR]

As a definition, Human–Machine Interface (HMI) enables a person to interact with a device. Starting from elementary equipment, the recent development of novel techniques and unobtrusive devices for biosignals monitoring paved the way for a new class of HMIs, which take such biosignals as inputs to control various applications. The current survey aims to review the large literature of the last two decades regarding biosignal-based HMIs for assistance and rehabilitation to outline state-of-the-art and identify emerging technologies and potential future research trends. PubMed and other databases were surveyed by using specific keywords. The found studies were further screened in three levels (title, abstract, full-text), and eventually, 144 journal papers and 37 conference papers were included. Four macrocategories were considered to classify the different biosignals used for HMI control: biopotential, muscle mechanical motion, body motion, and their combinations (hybrid systems). The HMIs were also classified according to their target application by considering six categories: prosthetic control, robotic control, virtual reality control, gesture recognition, communication, and smart environment control. An ever-growing number of publications has been observed over the last years. Most of the studies (about 67%) pertain to the assistive field, while 20% relate to rehabilitation and 13% to assistance and rehabilitation. A moderate increase can be observed in studies focusing on robotic control, prosthetic control, and gesture recognition in the last decade. In contrast, studies on the other targets experienced only a small increase. Biopotentials are no longer the leading control signals, and the use of muscle mechanical motion signals has experienced a considerable rise, especially in prosthetic control. Hybrid technologies are promising, as they could lead to higher performances. However, they also increase HMIs' complexity, so their usefulness should be carefully evaluated for the specific application. [ABSTRACT FROM AUTHOR]

Placental abruption is the separation of the placenta from the lining of the uterus before childbirth. It is an infrequent perinatal complication with serious after-effects and a marked risk of maternal and fetal mortality. Despite the fact that numerous placental abruption risk factors are known, the pathophysiology of this issue is multifactorial and not entirely clear. The aim of this review was to examine the current state of knowledge concerning the molecular changes on the maternal–fetal interface occurring in placental abruption. Only original research articles describing studies published in English until the 15 March 2021 were considered eligible. Reviews, book chapters, case studies, conference papers and opinions were excluded. The systematic literature search of PubMed/MEDLINE and Scopus databases identified 708 articles, 22 of which were analyzed. The available evidence indicates that the disruption of the immunological processes on the maternal–fetal interface plays a crucial role in the pathophysiology of placental abruption. The features of chronic non-infectious inflammation and augmented immunological cytotoxic response were found to be present in placental abruption samples in the reviewed studies. Various molecules participate in this process, with only a few being examined. More advanced research is needed to fully explain this complicated process. [ABSTRACT FROM AUTHOR]

Deterioration of bridge infrastructure is a serious concern to transport and government agencies as it declines serviceability and reliability of bridges and jeopardizes public safety. Maintenance and rehabilitation needs of bridge infrastructure are periodically monitored and assessed, typically every two years. Existing inspection techniques, such as visual inspection, are time-consuming, subjective, and often incomplete. Non-destructive testing (NDT) using Unmanned Aerial Vehicles (UAVs) have been gaining momentum for bridge monitoring in the recent years, particularly due to enhanced accessibility and cost efficiency, deterrence of traffic closure, and improved safety during inspection. The primary objective of this study is to conduct a comprehensive review of the application of UAVs in bridge condition monitoring, used in conjunction with remote sensing technologies. Remote sensing technologies such as visual imagery, infrared thermography, LiDAR, and other sensors, integrated with UAVs for data acquisition are analyzed in depth. This study compiled sixty-five journal and conference papers published in the last two decades scrutinizing NDT-based UAV systems. In addition to comparison of stand-alone and integrated NDT-UAV methods, the facilitation of bridge inspection using UAVs is thoroughly discussed in the present article in terms of ease of use, accuracy, cost-efficiency, employed data collection tools, and simulation platforms. Additionally, challenges and future perspectives of the reviewed UAV-NDT technologies are highlighted. [ABSTRACT FROM AUTHOR]

Scarce and niche in the literature just a few years ago, the blockchain topic is now the main subject in conference papers and books. However, the hype generated by the technology and its potential implications for real-world applications is flawed by many misconceptions about how it works and how it is implemented, creating faulty thinking or overly optimistic expectations. Too often, characteristics such as immutability, transparency, and censorship resistance, which mainly belong to the bitcoin blockchain, are sought in regular blockchains, whose potential is barely comparable. Furthermore, critical aspects such as oracles and their role in smart contracts receive few literature contributions, leaving results and theoretical implications highly questionable. This literature review of the latest papers in the field aims to give clarity to the blockchain oracle problem by discussing its effects in some of the most promising real-world applications. The analysis supports the view that the more trusted a system is, the less the oracle problem impacts. [ABSTRACT FROM AUTHOR]

The aim of this review was to summarize the available evidence about the use of levonorgestrel-releasing intrauterine system (LNG-IUS) as a contraceptive method in nulliparous women. For this purpose, studies evaluating the efficacy, safety, bleeding pattern, satisfaction and discontinuation of the levonorgestrel-releasing intrauterine system in nulliparous women were analyzed. Only original research articles published in English between 1990–27th March 2020 were considered eligible. Reviews, book chapters, case studies, conference papers, opinions, editorials and letters were excluded. The systematic literature search of PubMed/MEDLINE, Scopus, Embase and Cochrane Library databases identified 816 articles, 23 of which were analyzed. The available evidence indicates that LNG-IUS is an effective and safe contraceptive method for nulliparous women that achieves high levels of satisfaction among patients. Moreover, nulliparous women seem to experience fewer expulsions than parous ones. Bleeding pattern is acceptable for the majority of patients, and bleeding disorders mainly occur in the first months after the insertion. More in-depth, long-term prospective studies are needed in this patient group to determine risk factors for the occurrence of side effects and associated discontinuations, which should not, however, delay the wider use of the method in this group, given the number of advantages. [ABSTRACT FROM AUTHOR]